Building a pipeline and tutorial for task fMRI analysis in nistats and functional connectivity analysis in nilearn
Human Connectome Project N-back task fMRI data (N = 35)
Emotional Music (N = 21; 11 controls and 10 patients w/ MDD)
Within each run, the 4 different image types are presented in separate blocks within the run. Within each run, ½ of the blocks use a 2-back working memory task (respond ‘target’ whenever the current stimulus is the same as the one two back) and ½ use a 0-back working memory task (a target cue is presented at the start of each block (Barch et al. 2013, NeuroImage; Moser et al. 2017, Molecular Psychiatry).
Participants listened to blocks of positive and negative music. (2x2 matrix: MDD vs. control; postive vs. negative music) (Lepping et al. 2016, PLOS ONE)
Data processing and signal extraction
Whole brain connectivity analysis for HCP
Peak ROI connectivity analysis for emotional music
Whole brain connectivity analysis for emotional music
- tfMRI_WM_RL.nii.gz <- BOLD data for run 1
- Smoothing
- Define the design matrix using onset timing
- Conduct GLM (including appropriate confounds)
- Compute contrasts (e.g., 2back, 0back, and 2back vs. 0back)
- Save z_maps and peak ROI coordinates
- Peak ROI connectivity analysis
- Whole brain connectivity analysis